To solve this problem, inspired by other urban analysis studies [1]}, [2]}, [3]}, [4]}, we want to build a visual analysis system to provide prediction with interpretation and additional related information. As the system needs an interpretation method, we employ the Shapley value, proposed by Shapley [5]} and adopted in [6]}. The Shapley value is widely considered a unique unbiased approach to fairly allocating the total award a coalition to each input feature. In the traffic flow prediction task, we use the Shapely value to quantify the correlations between the prediction results in the selected region and actual traffic flow or geography area. Then we propose TrafPS, a visual analysis system interpreting traffic prediction in Shapley, to enhance the urban expert on analyzing traffic prediction and reacting to potential traffic jams.
